Bidirectional Mendelian Randomization of Causal Relationship between Inflammatory Cytokines and Different Pathological Types of Lung Cancer

Prior research has proposed a potential association between lung cancer and inflammatory cytokines, yet the specific causal relationship remains unclear, especially across various lung cancer pathologies. This study utilized bidirectional Mendelian randomization (MR) to explore these causal connections, unveiling novel insights. Our research revealed distinctive inflammatory cytokine profiles for each subtype of lung cancer and identified potential biomarkers that could refine diagnostic and therapeutic approaches. We applied two-sample Mendelian randomization, leveraging genetic variance data from three extensive genome-wide association studies (GWAS) focusing on different lung cancer types (lung adenocarcinoma: 1590 cases and 314,193 controls of healthy individuals of European descent; lung squamous cell carcinoma: 1510 cases and 314,193 controls of European ancestry; small cell lung cancer: 717 cases and 314,193 controls of European ancestry). A separate GWAS summary on inflammatory cytokines from 8,293 healthy participants was also included. The inverse variance weighting method was utilized to examine causal relationships, with robustness confirmed through multiple sensitivity analyses, including MR-Egger, weighted median, and MR-PRESSO. Our analysis revealed that elevated levels of IL_1RA were associated with an increased risk of lung adenocarcinoma (OR: 1.29, 95% CI: 1.02-1.64, p = 0.031), while higher MCP_1_MCAF levels correlated with a decreased risk of lung squamous cell carcinoma (OR: 0.77, 95% CI: 0.61-0.98, p = 0.031). Furthermore, IL_10, IL_13, and TRAIL levels were positively associated with lung squamous cell carcinoma risk (IL_10: OR: 1.27, 95% CI: 1.06-1.53, p = 0.012; IL_13: OR: 1.15, 95% CI: 1.06-1.53, p = 0.036; TRAIL: OR: 1.15, 95% CI: 1.06-1.53, p = 0.043). No association was found between inflammatory cytokine levels and small cell lung cancer development, whereas SDF_1A and B-NGF were linked to an increased risk of this cancer type (SDF_1A: OR: 1.13, 95% CI: 1.05-1.21, p = 0.001; B-NGF: OR: 1.13, 95% CI: 1.01-1.27, p = 0.029). No significant relationship was observed between the 41 circulating inflammatory cytokines and lung adenocarcinoma or squamous cell carcinoma development. Our findings indicate distinct associations between specific inflammatory cytokines and different types of lung cancer. Elevated IL_1RA levels are a risk marker for lung adenocarcinoma, whereas higher MCP_1_MCAF levels appear protective against lung squamous cell carcinoma. Conversely, elevated levels of IL_10, IL_13, and TRAIL are linked with an increased risk of lung squamous cell carcinoma. The relationships of SDF_1A and B-NGF with small-cell lung cancer highlight the complexity of inflammatory markers in cancer development. This study provides a nuanced understanding of the role of inflammatory cytokines in lung cancer, underscoring their potential in refining diagnosis and treatment strategies.


Figure S2
Funnel plots of Forward Mendelian randomization (MR) analyses for MCP-1 IL-10 IL-13 and TRAIL in squamous cell lung carcinoma which was applied to detect whether the observed association was along with obvious heterogeneity: (A) A funnel plot of the association between MCP-land squamous cell lung carcinoma.(B) A funnel plot of the association between IL-10 and squamous cell lung carcinoma.(C) A funnel plot of the association between IL-13 and squamous cell lung carcinoma.: (D) A funnel plot of the association between TRAIL and squamous cell lung carcinoma.

Figure S3
Forest plots of Forward Mendelian randomization (MR)analyses for MCP-1 IL-10 IL-13 and TRAIL in squamous cell lung carcinoma which was used to show the MR estimate and 95%CI values (gray line segment for each SNP which also shows the IVW and MR-Egger results at the bottom:(A) A forest plot of the association between MCPland squamous cell lung carcinoma.(B) A forest plot of the association between IL-10 and squamous cell lung carcinoma.(C) A forest plot of the association between IL-13 and squamous cell lung carcinoma.(D) A forest plot of the association between TRAIL and squamous cell lung carcinoma.

Figure S4
Leave-one-out analyses of Forward Mendelian randomization (MR) analyses for MCP-1, IL-10, IL-13 and TRAIL in squamous cell lung carcinoma to evaluate whether any single instrumental variable was driving the causal effect: (A) Leave-one-out analyses between MCP-1 and squamous cell lung carcinoma; (B) Leave-one-out analyses between IL-10 and squamous cell lung carcinoma; (C) Leave-one-out analyses between IL-13 and squamous cell lung carcinoma; (D)Leave-one-out analyses between TRAIL and squamous cell lung carcinoma.

Figure S6
Funnel plots of Reverse Mendelian randomization (MR) analyses for B-NGF and SDF-1A in squamous cell lung carcinoma which was applied to detect whether the observed association was along with obvious heterogeneity: (A) A funnel plot of the association between B-NGF and squamous cell lung carcinoma; (B) A funnel plot of the association between SDF-1A and squamous cell lung carcinoma.

Figure S1
Figure S1Funnel plots and forest plots of Forward Mendelian randomization (MR) analyses for IL-IRA in lung adenocarcinoma: (A)Funnel plot was applied to detect whether the observed association was along with obvious heterogeneity.(B) Forest plot was used to show the MR estimate and 95% CI values (gray line segment) for each SNP which also shows the IVW and MR-Egger results at the bottom.(C) Leave-one-out analyses to evaluate whether any single instrumental variable was driving the causal effect.

Figure S7
Figure S7Forest plots of Reverse Mendelian randomization (MR) analyses for B-NGF and SDF-1A in squamous cell lung carcinoma used to show the MR estimate and 95%CI values (gray line segment) for each SNP which also shows the IVW and MR-Egger results at the bottom: (A) A Forest plot of the association between B-NGF and squamous cell lung carcinoma.(B) A Forest plot of the association between SDF-1A and squamous cell lung carcinoma.

Figure
Figure S8Leave-one-out analyses of Reverse Mendelian randomization (MR) analyses for B-NGF and SDF-A in squamous cell lung carcinoma to evaluate whether any single instrumental variable was driving the causal effect: (A) Leaveone-out analyses of the association between B-NGF and squamous cell lung carcinoma; (B) Leave-one-out analyses of the association between SDF-1A and squamous cell lung carcinoma.

Figure S10 .
Figure S10.Results of Reverse Mendelian randomization of inflammatory cytokines and squamous cell lung carcinoma